Skip to main content
Log in

Efficient computation of map algebra over raster data stored in the k2-acc compact data structure

  • Published:
GeoInformatica Aims and scope Submit manuscript

Abstract

We present efficient algorithms to compute simple and complex map algebra operations over raster data stored in main memory, using the k2-acc compact data structure. Raster data correspond to numerical data that represent attributes of spatial objects, such as temperature or elevation measures. Compact data structures allow efficient data storage in main memory and query them in their compressed form. A k2-acc is a set of k2-trees, one for every distinct numeric value in the raster matrix. We demonstrate that map algebra operations can be computed efficiently using this compact data structure. In fact, some map algebra operations perform over five orders of magnitude faster compared with algorithms working over uncompressed datasets.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. A data warehouse is a data repository that stores consolidate data of a business to improve the decisions-making process.

  2. If the matrix is n × m with n and m any integer, we conceptually extend the input matrix to the right and to the bottom with 0s, that is, we round n and m up to the next power of k of their maximum value.

  3. The repositories are, respectively, available at http://gitlab.face.ubiobio.cl:8081/18978826/algebra-de-mapas-sobre-k2-acc/tree/master/K2TreeAccum and https://gitlab.lbd.org.es/fsilva/k2-raster

  4. https://gitlab.citius.usc.es/ruben.laso/K3-tree-optimization/-/tree/master/Data/Original

  5. https://search.asf.alaska.edu

References

  1. Álvarez-García S, de Bernardo G, Brisaboa N, Navarro G (2017) A succinct data structure for self-indexing ternary relations. J Discrete Algorithm 43:38–53

    Article  MathSciNet  Google Scholar 

  2. Anselin L, Bao S (1997) Exploratory spatial data analysis linking SpaceStat and ArcView. Springer

  3. de Bernardo G, Álvarez-García S, Brisaboa N, Navarro G, Pedreira O (2013) Compact querieable representations of raster data. In: Proceedings of the International Symposium on String Processing and Information Retrieval, pp 96–108

  4. Brisaboa N, de Bernardo G, Gutiérrez G, Luaces M, Paramá J (2017) Efficiently querying vector and raster data. Comput J 60(9):1395–1413

    Article  MathSciNet  Google Scholar 

  5. Brisaboa N, de Bernardo G, Konow R, Navarro G (2014) K2-treaps: range top-k queries in compact space. In: Proceedings of the 21st International Symposium on String Processing and Information Retrieval, pp 215–226

  6. Brisaboa N, Cerdeira-pena A, de Bernardo G, Navarro G, Pedreira O (2020) Extending general compact querieable representations to GIS, applications. Inf Sci 506:196–216

    Article  Google Scholar 

  7. Brisaboa N, Cerdeira-Pena A, López-López N, Navarro G, Penabad M, Silva-coira F (2016) Efficient representation of multidimensional data over hierarchical domains. In: Proceedings of the 23rd International Symposium on String Processing and Information Retrieval, pp 191–203

  8. Brisaboa N, Ladra S, Navarro G (2009) K2-trees for compact web graph representation. In: Proceedings of the 16th International Symposium on String Processing and Information Retrieval, pp. 18–30

  9. Brisaboa N, Ladra S, Navarro G (2013) Dacs: Bringing direct access to variable-length codes. Inf Process Manag 49(1):392–404

    Article  Google Scholar 

  10. Brisaboa N, Ladra S, Navarro G (2014) Compact representation of web graphs with extended functionality. Inf Syst 39:152–174

    Article  Google Scholar 

  11. Brisaboa N, Luaces M, Navarro G, Seco D (2010) A fun application of compact data structures to indexing geographic data. In: Proceedings of the International Conference on Fun with Algorithms, pp 77–88

  12. Brisaboa N, Luaces M, Navarro G, Seco D (2013) Space-efficient representations of rectangle datasets supporting orthogonal range querying. Inf Syst 38 (5):635–655

    Article  Google Scholar 

  13. Castro JF, Romero M, Gutiėrrez G, Caniupȧn M, Quijada-fuentes C (2020) Efficient computation of the convex hull on sets of points stored in a k-tree compact data structure. Knowl Inf Syst 62(10):4091–4111

    Article  Google Scholar 

  14. Cerveira J, Camara G, Moura U, Almeida F (2009) Yet another map algebra. Geoinformatica 13:183–202

    Article  Google Scholar 

  15. Claude F, Navarro G (2007) A fast and compact web graph representation. In: Proceedings of the 14th International Symposium on String Processing and Information Retrieval (SPIRE), Lecture Notes in Computer Science, vol 4726, pp 105–116

  16. Claude F, Navarro G (2009) Practical rank/select queries over arbitrary sequences. In: Proceedings of the 15th International Symposium on String Processing and Information Retrieval, pp 176–187

  17. Fariña A, Ladra S, Pedreira O, Places Á (2009) Rank and select for succinct data structures. Electron Notes Theor Comput Sci 236:131–145

    Article  Google Scholar 

  18. Guttman A (1984) R-trees: a dynamic index structure for spatial searching. In: Proceedings of SIGMOD, pp 47–57

  19. Ishiyama K, Kobayashi K, Sadakane K (2017) Succinct quadtrees for road data. In: Proceedings of the International Conference on Similarity Search and Applications, pp 262–272

  20. Jeremy M, Dana T (2005) Cubic map algebra functions for spatio-temporal analysis. Cartogr Geogr Inf Sci 32:17–32

    Article  Google Scholar 

  21. Ladra S, Paramȧ J, Silva-coira F (2016) Compact and queryable representation of raster datasets. In: Proceedings of the 28th International Conference on Scientific and Statistical Database Management, pp 15:1–15:12

  22. Linco F, Caniupán M (2018) Extending the cmhd compact data structure to compute aggregations over data warehouses. In: Proceeding of the international conference of the chilean computer science society, pp 1–8

  23. Manolopoulos Y, Nanopoulos A, Papadopoulos A, Theodoridis Y (2010) R-trees: theory and applications. Springer Science and Business Media

  24. Navarro G (2014) Spaces, trees, and colors: The algorithmic landscape of document retrieval on sequences. ACM Comput Surv 46(4):52:1–52:47

    Article  Google Scholar 

  25. Navarro G (2014) Wavelet trees for all. J Discret Algorithm 25:2–20

    Article  MathSciNet  Google Scholar 

  26. Navarro G (2016) Compact data structures: a practical approach. Cambridge University Press

  27. Pinto A, Seco D, Gutiérrez G (2017) Improved queryable representations of rasters. In: Data compression conference, pp 320–329

  28. Quijada-Fuentes C, Ladra S, Gutiérrez G (2019) Set operations over compressed binary relations. Inf Syst 80:76–90

    Article  Google Scholar 

  29. Shelkhar S, Chawla S (2013) Spatial Databases a Tour, 1st edn. Prentice Hall

  30. Silva-Coria F, Parama J, Ladra S, Lopez J, Gutiérrez G (2020) Efficient processing of raster and vector data. Plos One 15:e0226,943

    Article  Google Scholar 

  31. Tomlin D (2012) GIS And cartographic modeling. Esri Press

  32. Vallejos C, Caniupán M, Gutiérrez G (2018) Compact data structures to represent and query data warehouses into main memory. IEEE Lat Am Trans 16(9):2328–2335

    Article  Google Scholar 

  33. Venkat P, Mount D (2014) A succinct, dynamic data structure for proximity queries on point sets. In: Proceedings of the Canadian Conference on Computational Geometry

Download references

Acknowledgements

Mónica Caniupán is partially funded by projects DIUBB [181315 3/R] and [2030228 If/R]. Rodrigo Torres-Avilés is partially funded by project DIUBB [181315 3/R]. The authors are part of the Algorithms and Databases Research Group [195119 GI/VC]. We would like to thank the useful conversations with some of the authors of the k2-raster.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mónica Caniupán.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Caniupán, M., Torres-Avilés, R., Gutiérrez-Bunster, T. et al. Efficient computation of map algebra over raster data stored in the k2-acc compact data structure. Geoinformatica 26, 95–123 (2022). https://doi.org/10.1007/s10707-021-00445-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10707-021-00445-y

Keywords

Navigation